Get started with queries and visualizations

Queries and visualizations support
the iterative nature of qualitative research and help you to investigate
hunches as you progress through your project.

It is a good idea to start running
queries early on—they can help you focus on the questions you want to
ask (and prompt you to code accordingly). They can also help you
to determine whether you need to gather additional sources of data or
re-frame the questions you are asking.

To start with, you may want to run
some simple queries and preview the results—refer to About
queries to get up and running. As you grow in confidence, you can
look at building more complex criteria and storing your results in nodes.

When you begin using queries it can
help to remember:

Coding
queries rely on the work you have done— patchy or inconsistent coding
may yield less useful results.

Review
the query results and make a memo to describe how it contributes to
your understanding.

While
queries and visualizations can give you different perspectives on
your data, you will still need to use your analytical skills to interpret
the results.

Saved
queries can act as 'signposts' for future investigation, set them
up early and rerun them as you progress through your project.

Query and visualize during your literature review

You can use NVivo for your literature review—and as
your project progresses, you may return to the literature to see where
your findings support or contradict those of other authors. As you conduct
your literature review, you might use the following queries to explore
the material:

Query and visualize during data analysis (coding)

Early on in your project, Text
Search and Word
Frequency queries can help you to organize your data into broad categories.
For example, you could use a Text Search query to search for real
estate development and automatically code all of the occurrences.

As you move
into more detailed coding and continue to organize or 'segment' your data
by theme—queries can help you to reassemble and examine the themes in
ways that address your research question. For example, you may want to
explore the co-occurrence of themes
(show me content coded at development
AND water quality).

Rather than being a one-step process, querying your
coding is iterative—one query or visualization may lead to another as
you dig deeper into your data.

For example, to explore the idea that respondents
are pessimistic about real estate development, you might run the
following queries: